This report summarizes the results of an ongoing study focused on understanding the impact of the COVID-19 pandemic on Critical Care research. It includes data submitted by 126 centres between 2020-03-23 and 2020-07-14.
Participating centres
ICU location
map_world

| CAN |
37 |
| USA |
30 |
| AUS |
21 |
| FRA |
5 |
| NLD |
5 |
| NZL |
4 |
| ARG |
2 |
| GBR |
2 |
| IDN |
2 |
| ITA |
2 |
| MEX |
2 |
| SGP |
2 |
| THA |
2 |
| BRA |
1 |
| COL |
1 |
| DNK |
1 |
| ECU |
1 |
| IND |
1 |
| LBN |
1 |
| MYS |
1 |
| PAK |
1 |
| URY |
1 |
| VNM |
1 |
ICU population
dat_redcap %>%
select(record_id, site_pop) %>%
drop_na(site_pop) %>%
mutate(site_pop = recode(site_pop, "1" = "Adult", "2" = "Pediatric", "3" = "Mixed")) %>%
count(site_pop) %>%
mutate(perc = n.per(n, sum(n), 0),
label = paste(site_pop, "\n", perc, sep = "")
) %>%
mutate(order = row_number(),
fraction = n / sum(n),
label_pos = (cumsum(fraction) + c(0, head(cumsum(fraction), n = -1))) / 2) %>%
ggplot(aes(x = 2, y = fraction, fill = fct_reorder(label, rev(order)) )) +
geom_col(position = "fill", width = 1) +
geom_text(aes(label = label, y = label_pos, hjust = "outward"),
lineheight = 0.9, x = 2.75, size = 4) +
coord_polar("y", start = 0, clip = "off") +
scale_fill_brewer(palette = "Paired")+
scale_x_continuous(limits = c(0.05, 2.5))+
theme_void()+
theme(legend.position = "none")

Centre type
dat_redcap %>%
select(record_id, site_setting) %>%
drop_na(site_setting) %>%
mutate(site_setting = recode(site_setting, "1" = "Academic", "2" = "Community")) %>%
count(site_setting) %>%
mutate(perc = n.per(n, sum(n), 0),
label = paste(site_setting, "\n", perc, sep = "")
) %>%
mutate(order = row_number(),
fraction = n / sum(n),
label_pos = (cumsum(fraction) + c(0, head(cumsum(fraction), n = -1))) / 2) %>%
ggplot(aes(x = 2, y = fraction, fill = fct_reorder(label, rev(order)) )) +
geom_col(position = "fill", width = 1) +
geom_text(aes(label = label, y = label_pos, hjust = "outward"),
lineheight = 0.9, x = 2.75, size = 4) +
coord_polar("y", start = 0, clip = "off") +
scale_fill_brewer(palette = "Accent")+
scale_x_continuous(limits = c(0.05, 2.5))+
theme_void()+
theme(legend.position = "none")

Surveys per month
dat_redcap %>%
select(redcap_event_name) %>%
filter(redcap_event_name != "centre_info_arm_1") %>%
mutate(Month = case_when(
redcap_event_name == "202003_arm_1" ~ "March",
redcap_event_name == "202004_arm_1" ~ "April",
redcap_event_name == "202005_arm_1" ~ "May",
redcap_event_name == "202006_arm_1" ~ "June"
)) %>%
mutate(Month = fct_relevel(Month, c("March", "April", "May", "June"))) %>%
group_by(Month) %>%
drop_na() %>%
tally() %>%
select(Month, "Count" = n) %>%
kable()
| March |
107 |
| April |
104 |
| May |
101 |
| June |
91 |
# weekly_demo %>%
# kable()
COVID-19
Are there any patients in your hospital with CONFIRMED COVID-19? (n = 401 surveys)
ggplot(monthly_covid_hosp) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = covid_hosp),
colour = "white", size = 1) +
scale_fill_viridis_d(name = "") +
scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_covid_hosp$xcenter, labels = monthly_covid_hosp$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Are there any patients in your ICU with CONFIRMED COVID-19? (n = 401 surveys)
ggplot(monthly_covid_icu) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = covid_icu),
colour = "white", size = 1) +
scale_fill_viridis_d(name = "") +
scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_covid_icu$xcenter, labels = monthly_covid_icu$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Is your ICU currently enrolling patients in any COVID-19 specific studies? (n = 394 surveys)
ggplot(monthly_res_covid_any) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = res_covid_any),
colour = "white", size = 1) +
scale_fill_viridis_d(name = "") +
scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_res_covid_any$xcenter, labels = monthly_res_covid_any$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

What types of COVID-19 specific research studies are currently enrolling patients in your ICU? (n = 402 surveys) (Question added after start of the study)
dat_redcap %>%
filter(redcap_event_name %in% c("202003_arm_1", "202004_arm_1", "202005_arm_1", "202006_arm_1")) %>%
mutate(Month = recode(redcap_event_name,
"202003_arm_1" = "March 2020",
"202004_arm_1" = "April 2020",
"202005_arm_1" = "May 2020",
"202006_arm_1" = "June 2020"),
Month = fct_inorder(Month)) %>%
select(Month, "Randomized" = res_cov_type___1, "Non-randomized" = res_cov_type___2 , "Observational" = res_cov_type___3, "Other" = res_cov_type___4) %>%
mutate_at(c("Randomized", "Non-randomized", "Observational", "Other"), as.numeric) %>%
group_by(Month) %>%
summarise_at(c("Randomized", "Non-randomized", "Observational", "Other"),sum, na.rm= TRUE)%>%
kable(align = "c")
| March 2020 |
14 |
1 |
25 |
1 |
| April 2020 |
26 |
12 |
58 |
3 |
| May 2020 |
39 |
14 |
68 |
2 |
| June 2020 |
30 |
8 |
61 |
4 |
#This is the code I have trial but I am stuck here
#dat_redcap %>%
#filter(redcap_event_name != "centre_info_arm_1") %>%
#mutate(Month = recode(redcap_event_name,
#"202003_arm_1" = "March 2020",
#"202004_arm_1" = "April 2020",
#"202005_arm_1" = "May 2020",
#"202006_arm_1" = "June 2020"),
#Month = fct_inorder(Month)) %>%
#select(Month, record_id, "Randomized" = res_cov_type___1, "Non-randomized" = res_cov_type___2 , "Observational" = res_cov_type___3, "Other" = res_cov_type___4) %>%
#mutate_at(c("Randomized", "Non-randomized", "Observational", "Other"), as.numeric) %>%
#mutate("Site Count" = case_when(
#Randomized == 1 | `Non-randomized` == 1 | Observational == 1 | Other == 1 ~ 1,
#TRUE ~ 0
#)) %>%
#group_by(Month) %>%
#summarise_at(c("Randomized", "Non-randomized", "Observational", "Other", "Site Count"),sum, na.rm= TRUE)
#Comments
#dat_redcap %>%
#select(Other = res_cov_type_other) %>%
#drop_na(Other) %>%
#kable()
Is your ICU currently preparing for any COVID-19 specific studies? (Question added after start of the study)
ggplot(monthly_res_covid_any_prep) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = res_covid_any_prep),
colour = "white", size = 1) +
scale_fill_viridis_d(name = "") +
scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_res_covid_any_prep$xcenter, labels = monthly_res_covid_any_prep$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Institutional policies
Is your REB/IRB prioritizing approval or willing to expedite approval of COVID-19 protocols? (n = 402 surveys)
ggplot(monthly_covid_reb) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = covid_reb),
colour = "white", size = 2) +
scale_fill_manual(name = "", values = c("#F7977A", "#FFF79A", "#82CA9D"), guide = guide_legend(reverse = FALSE))+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_covid_reb$xcent, labels = monthly_covid_reb$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

# #require suspending enrolment in icu studies
# dat_redcap %>%
# filter(redcap_event_name %in% c("202003_arm_1", "202004_arm_1", "202005_arm_1", "202006_arm_1")) %>%
# mutate(Month = recode(redcap_event_name,
# "202003_arm_1" = "March 2020",
# "202004_arm_1" = "April 2020",
# "202005_arm_1" = "May 2020",
# "202006_arm_1" = "June 2020"),
# Month = fct_inorder(Month)) %>%
# select(Month, "Yes - All studies" = policy___1, "Yes - All non-COVID-19 studies" = policy___2 , "Yes - Some studies" = policy___3, "No" = policy___4, "Other" = policy___5) %>%
# mutate_at(c("Yes - All studies", "Yes - All non-COVID-19 studies", "Yes - Some studies", "Other"),
# as.numeric) %>%
# group_by(Month) %>%
# summarise_at(c("Yes - All studies", "Yes - All non-COVID-19 studies", "Yes - Some studies", "Other"),sum, na.rm= TRUE) %>%
# kable(align = "c")
#TABLE FOR THIS QUESTION
#Types of Studies that were affected?
#dat_redcap %>%
#select(Comments = policy_some_explain) %>%
#drop_na(Comments) %>%
#kable()
#Please explain the other requirements
#dat_redcap %>%
#select(Comments = policy_other) %>%
#drop_na(Comments) %>%
#kable()
Impact on research
Because of COVID-19 or preparation for it, has your ICU:
Suspended recruitment for any studies? (n = 402 surveys)
ggplot(monthly_effect_suspend) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_suspend),
colour = "white", size = 1) +
scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_effect_suspend$xcent, labels = monthly_effect_suspend$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

#dat_redcap %>%
#select(Comments = effect_suspend_explain) %>%
#drop_na(Comments) %>%
#kable()
Modified recruitment for current studies? (n = 401 surveys)
ggplot(monthly_effect_modify) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_modify),
colour = "white", size = 1) +
scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_effect_modify$xcent, labels = monthly_effect_modify$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

#Comments
#dat_redcap %>%
#select(Comments = effect_modify_explain) %>%
#drop_na(Comments) %>%
#kable()
Delayed the initiation of new (non-COVID-19) studies? (n = 400 surveys)
ggplot(monthly_effect_delay) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_delay),
colour = "white", size = 1) +
scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_effect_delay$xcent, labels = monthly_effect_delay$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

#Comments
#dat_redcap %>%
#select(Comments = effect_delay_explain) %>%
#drop_na(Comments) %>%
#kable()
Enrolled MORE patients in studies because of increased patient volume? (n = 401 surveys)
ggplot(monthly_effect_more) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_more),
colour = "white", size = 1) +
scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_effect_more$xcent, labels = monthly_effect_more$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

#Comments ADD THIS BACK IN IF THERE ARE COMMENTS
#dat_redcap %>%
#select(Comments = effect_more_explain) %>%
#drop_na(Comments) %>%
#kable()
Enrolled FEWER patients in studies because of increased patient volume? (n = 400 surveys)
ggplot(monthly_effect_less) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_less),
colour = "white", size = 1) +
scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_effect_less$xcent, labels = monthly_effect_less$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

#Comments
#dat_redcap %>%
#select(Comments = effect_less_explain) %>%
#drop_na(Comments) %>%
#kable()
Changed the approach to co-enrollment in studies? (n = 400 surveys)
ggplot(monthly_effect_co) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_co),
colour = "white", size = 1) +
scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_effect_co$xcent, labels = monthly_effect_co$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

#Comments
#dat_redcap %>%
#select(Comments = effect_co_explain) %>%
#drop_na(Comments) %>%
#kable()
Changed or stopped collection of biologic samples? (n = 400 surveys)
ggplot(monthly_effect_bio) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_bio),
colour = "white", size = 1) +
scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_effect_bio$xcent, labels = monthly_effect_bio$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

#Comments
#dat_redcap %>%
#select(Comments = effect_bio_explain) %>%
#drop_na(Comments) %>%
#kable()
Other effects on studies in your ICU? (n = 388 surveys)
ggplot(monthly_effect_other_yn) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_other_yn),
colour = "white", size = 1) +
scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_effect_other_yn$xcent, labels = monthly_effect_other_yn$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

#Comments
#dat_redcap %>%
#select(Comments = effect_other) %>%
#drop_na(Comments) %>%
#kable()
Reasons for impact
Because of COVID-19 or preparation for it, how much of an effect have the following had on research in your ICU?
Research staff WITH a clinical background are needed to work clinically (n = 401 surveys)
ggplot(monthly_reason_clinwork) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_clinwork),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_clinwork$xcent, labels = monthly_reason_clinwork$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Research staff WITHOUT a clinical background are needed to help with hospital activities (n = 400 surveys)
ggplot(monthly_reason_work) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_work),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_work$xcent, labels = monthly_reason_work$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Investigators are needed to work clinically (n = 307 surveys) (Question added after start of the study)
ggplot(monthly_reason_clinwork_invest) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_clinwork_invest),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_clinwork_invest$xcent, labels = monthly_reason_clinwork_invest$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Research staff are concerned about their safety working during outbreak (n = 400 surveys)
ggplot(monthly_reason_safety) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_safety),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_safety$xcent, labels = monthly_reason_safety$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Your pediatric ICU is admitting (or planning to admit) adults (n = 185 surveys) (Question added after start of the study)
ggplot(monthly_reason_adults) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_adults),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_adults$xcent, labels = monthly_reason_adults$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic
Error in grid.Call.graphics(C_setviewport, vp, TRUE) :
non-finite location and/or size for viewport

Not enough research staff for increased number of COVID-19 studies (n = 396 surveys)
ggplot(monthly_reason_numstudies) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_numstudies),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_numstudies$xcent, labels = monthly_reason_numstudies$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Not enough research staff for increased number of eligible patients (n = 400 surveys)
ggplot(monthly_reason_numpts) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_numpts),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_numpts$xcent, labels = monthly_reason_numpts$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Infection control policies limiting research staff access to the ICU (n = 399 surveys)
ggplot(monthly_reason_accessicu) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_accessicu),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_accessicu$xcent, labels = monthly_reason_accessicu$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Infection control policies limiting research staff access to patients with confirmed or suspected COVID-19 (n = 400 surveys)
ggplot(monthly_reason_accesspt) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_accesspt),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_accesspt$xcent, labels = monthly_reason_accesspt$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Clinical staff are too busy to complete research-related tasks (n = 400 surveys)
ggplot(monthly_reason_clinworkload) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_clinworkload),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_clinworkload$xcent, labels = monthly_reason_clinworkload$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

Research facilities for processing or storage of biological samples are closed or have reduced capacity (n = 341 surveys) (Question added after start of the study)
ggplot(monthly_reason_lab) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_lab),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_lab$xcent, labels = monthly_reason_lab$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

COVID-19 specific research is prioritized over other research (n = 398 surveys)
ggplot(monthly_reason_priorities) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_priorities),
colour = "white", size = 1) +
scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE),
direction = -1)+
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
expand = c(0, 0)) +
scale_x_continuous(breaks = monthly_reason_priorities$xcent, labels = monthly_reason_priorities$month,
expand = c(0, 0)) +
coord_fixed() +
theme_bw() +
theme_mosaic

#dat_redcap %>%
#select(Comments = reason_other) %>%
#drop_na(Comments) %>%
#kable()
To join this study
On behalf of the Canadian Critical Care Trials Group and Canadian Critical Care Research Coordinators group, we invite your site to participate in a short longitudinal survey of the effects of COVID-19 on critical care research.
Use this link to send us the name and email of the person who will complete the survey on behalf of your centre: http://bit.ly/3aNqo8Z
They’ll receive a separate email with the survey within 24 hours and will get:
1) A 3-question survey about your ICU
2) A short (<10 min) monthly survey about the impact of COVID-19 on research in your ICU
About this study
Background: As we prepare for and manage COVID-19 patients in our ICUs, we realize both the importance of studying this disease and our role as global leaders in critical care research. From our experiences with SARS and H1N1, we also know that COVID-19 may both enhance and constrain current critical care research projects.
Objectives: The aims of this study are to:
1. Characterize current research activities in ICUs
2. Describe the effects of COVID-19 (and preparations) on research in ICUs, specifically to: identify new research started due to COVID-19; describe any impact on existing research activities; and identify COVID-19 hospital or ICU policies affecting research.
Methods: If you agree for your site to participate, you or your delegate will receive:
• A link to a single, brief survey (3 questions) about your ICU
• A link to a short (<10 minutes) survey about the impact of COVID-19 on research in your ICU. It will be sent on the first of the month for the duration of the COVID-19 outbreak.
• A report summarizing the results after each monthly survey
Ethics and privacy: This study has been reviewed by the Hamilton Integrated Research Ethics Board. Participation is of course voluntary and submitting data implies your consent to participate . You can stop participating at any time and prior to analysis you can withdraw any data from your centre. We will not publish any site or personal identifying information without your express consent.
Thank you, and we welcome any suggestions for adapting and updating this survey as events in this pandemic unfold.
Mark Duffett, RPh PhD
Departments of Pediatrics and Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada. duffetmc@mcmaster.ca, @M_Duffett
Michelle Kho, PT PhD
School of Rehabilitation Science, McMaster University, Hamilton, Canada. khome@mcmaster.ca, @khome
---
title: "Impact of COVID-19 on critical care research"
output:
  html_notebook:
    code_folding: hide
    toc: yes
    toc_float: yes
  html_document:
    df_print: paged
    toc: yes
  pdf_document:
    toc: yes
---


```{r setup, include=FALSE}

# load packages (other packages loaded with sourced files)
library(knitr)

# # source files
# # sourcing not working...problem with working directory. So run files manually for now: Run sourcing in COVID-19 Survey report - sourcing files.R)

# set options
opts_knit$set(root.dir = rprojroot::find_rstudio_root_file())
opts_chunk$set(echo=FALSE, warning=FALSE, message=FALSE, include=TRUE)

# library(tidyverse)
# library(RColorBrewer)
# library(sf)
# library(rnaturalearth)
# library(rnaturalearthdata)
# library(rgeos)
# library(tinytex)
# library(lubridate)
```
  
This report summarizes the results of an ongoing study focused on understanding the impact of the COVID-19 pandemic on Critical Care research. It includes data submitted by `r nrow(dat_centre)` centres between `r min(dat_date$research_impact_timestamp, na.rm = TRUE) ` and `r max(dat_date$research_impact_timestamp, na.rm = TRUE)`. 

<!-- Tabs not working -->
<!--makes tabs out of subheadings-->  
<!-- # {.tabset .tabset-fade .tabset-pills}   -->

<!--tab 1------------------------------------------------------->  
## Participating centres  
***  
### ICU location
```{r fig.fullwidth = TRUE}
map_world
```

```{r countries, echo = FALSE}
dat_centre %>% 
  count(Country_Code_3) %>% 
  arrange(desc(n)) %>% 
  select(Country = Country_Code_3, ICUs = n) %>% 
  kable()
```

***  
### ICU population  
```{r}
dat_redcap %>% 
  select(record_id, site_pop) %>% 
  drop_na(site_pop) %>% 
  mutate(site_pop = recode(site_pop, "1" = "Adult", "2" = "Pediatric", "3" = "Mixed")) %>% 
    count(site_pop) %>% 
  mutate(perc = n.per(n, sum(n), 0),
         label = paste(site_pop, "\n", perc, sep = "")
         ) %>% 
  mutate(order = row_number(),
         fraction = n / sum(n),
         label_pos = (cumsum(fraction) + c(0, head(cumsum(fraction), n = -1))) / 2) %>% 
ggplot(aes(x = 2, y = fraction, fill = fct_reorder(label, rev(order)) )) +
  geom_col(position = "fill", width = 1) +
  geom_text(aes(label = label, y = label_pos, hjust = "outward"), 
            lineheight = 0.9, x = 2.75, size = 4) +
  coord_polar("y", start = 0, clip = "off") +
  scale_fill_brewer(palette = "Paired")+
  scale_x_continuous(limits = c(0.05, 2.5))+
  theme_void()+
  theme(legend.position = "none")

```

***  
### Centre type  
```{r}
dat_redcap %>% 
  select(record_id, site_setting) %>% 
  drop_na(site_setting) %>% 
  mutate(site_setting = recode(site_setting, "1" = "Academic", "2" = "Community")) %>% 
    count(site_setting) %>% 
  mutate(perc = n.per(n, sum(n), 0),
         label = paste(site_setting, "\n", perc, sep = "")
         ) %>% 
  mutate(order = row_number(),
         fraction = n / sum(n),
         label_pos = (cumsum(fraction) + c(0, head(cumsum(fraction), n = -1))) / 2) %>% 
ggplot(aes(x = 2, y = fraction, fill = fct_reorder(label, rev(order)) )) +
  geom_col(position = "fill", width = 1) +
  geom_text(aes(label = label, y = label_pos, hjust = "outward"), 
            lineheight = 0.9, x = 2.75, size = 4) +
  coord_polar("y", start = 0, clip = "off") +
  scale_fill_brewer(palette = "Accent")+
  scale_x_continuous(limits = c(0.05, 2.5))+
  theme_void()+
  theme(legend.position = "none")

```
 
 
***
### Surveys per month

```{r}
dat_redcap %>%
  select(redcap_event_name) %>%
  filter(redcap_event_name != "centre_info_arm_1") %>%
  mutate(Month = case_when(
    redcap_event_name == "202003_arm_1" ~ "March",
    redcap_event_name == "202004_arm_1" ~ "April",
    redcap_event_name == "202005_arm_1" ~ "May",
    redcap_event_name == "202006_arm_1" ~ "June"
  )) %>%
  mutate(Month = fct_relevel(Month, c("March", "April", "May", "June"))) %>%
  group_by(Month) %>%
  drop_na() %>%
  tally() %>%
  select(Month, "Count" = n) %>%
  kable()
```
   
    
```{r}
# weekly_demo %>%  
#   kable()
```
  
<!--tab 3------------------------------------------------------->  
***  
## COVID-19  

***
**Are there any patients in your hospital with CONFIRMED COVID-19?** (n = `r sum(!is.na(dat_redcap$covid_hosp))` surveys)

```{r fig.height=6, fig.width=6, results = "hold"}
ggplot(monthly_covid_hosp) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = covid_hosp), 
            colour = "white", size = 1) +
  scale_fill_viridis_d(name = "") +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_covid_hosp$xcenter, labels = monthly_covid_hosp$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
```

***
**Are there any patients in your ICU with CONFIRMED COVID-19?** (n = `r sum(!is.na(dat_redcap$covid_hosp))` surveys)

```{r fig.height=6, fig.width=6, results = "hold"}
ggplot(monthly_covid_icu) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = covid_icu), 
            colour = "white", size = 1) +
  scale_fill_viridis_d(name = "") +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_covid_icu$xcenter, labels = monthly_covid_icu$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
```
***
**Is your ICU currently enrolling patients in any COVID-19 specific studies?** (n = `r sum(!is.na(dat_redcap$res_covid_any))` surveys)

```{r fig.height=6, fig.width=6, results = "hold"}
ggplot(monthly_res_covid_any) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = res_covid_any), 
            colour = "white", size = 1) +
  scale_fill_viridis_d(name = "") +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_res_covid_any$xcenter, labels = monthly_res_covid_any$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

```

***
**What types of COVID-19 specific research studies are currently enrolling patients in your ICU?** (n = `r sum(!is.na(dat_redcap$covid_reb))` surveys) (Question added after start of the study) 

```{r}
dat_redcap %>% 
  filter(redcap_event_name %in% c("202003_arm_1", "202004_arm_1", "202005_arm_1", "202006_arm_1")) %>%
  mutate(Month = recode(redcap_event_name, 
                        "202003_arm_1" = "March 2020", 
                        "202004_arm_1" = "April 2020", 
                        "202005_arm_1" = "May 2020",
                        "202006_arm_1" = "June 2020"),
         Month = fct_inorder(Month)) %>%
  select(Month, "Randomized" = res_cov_type___1, "Non-randomized" = res_cov_type___2 , "Observational" = res_cov_type___3, "Other" = res_cov_type___4) %>%
  mutate_at(c("Randomized", "Non-randomized", "Observational", "Other"), as.numeric) %>%
  group_by(Month) %>%
  summarise_at(c("Randomized", "Non-randomized", "Observational", "Other"),sum, na.rm= TRUE)%>%
  kable(align = "c")

#This is the code I have trial but I am stuck here
#dat_redcap %>% 
 #filter(redcap_event_name != "centre_info_arm_1") %>%
  #mutate(Month = recode(redcap_event_name, 
                        #"202003_arm_1" = "March 2020", 
                        #"202004_arm_1" = "April 2020", 
                        #"202005_arm_1" = "May 2020",
                        #"202006_arm_1" = "June 2020"),
        #Month = fct_inorder(Month)) %>%
  #select(Month, record_id,  "Randomized" = res_cov_type___1, "Non-randomized" = res_cov_type___2 , "Observational" = res_cov_type___3, "Other" = res_cov_type___4) %>%
  #mutate_at(c("Randomized", "Non-randomized", "Observational", "Other"), as.numeric) %>%
  #mutate("Site Count" = case_when(
    #Randomized == 1 | `Non-randomized` == 1 | Observational == 1 | Other == 1 ~ 1,
    #TRUE ~ 0
  #)) %>%
  #group_by(Month) %>%
  #summarise_at(c("Randomized", "Non-randomized", "Observational", "Other", "Site Count"),sum, na.rm= TRUE)


#Comments
#dat_redcap %>% 
  #select(Other = res_cov_type_other) %>% 
  #drop_na(Other) %>% 
  #kable()
```
***
**Is your ICU currently preparing for any COVID-19 specific studies?** (Question added after start of the study)

```{r fig.height=6, fig.width=6, results = "hold", warning=FALSE}

ggplot(monthly_res_covid_any_prep) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = res_covid_any_prep), 
            colour = "white", size = 1) +
  scale_fill_viridis_d(name = "") +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_res_covid_any_prep$xcenter, labels = monthly_res_covid_any_prep$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
```


<!--tab 6------------------------------------------------------->  
## Institutional policies 

***
**Is your REB/IRB prioritizing approval or willing to expedite approval of COVID-19 protocols?** (n = `r sum(!is.na(dat_redcap$covid_reb))` surveys)

```{r fig.height=6, fig.width=6, results = "hold", warning=FALSE}
ggplot(monthly_covid_reb) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = covid_reb), 
            colour = "white", size = 2) +
  scale_fill_manual(name = "", values = c("#F7977A", "#FFF79A", "#82CA9D"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_covid_reb$xcent, labels = monthly_covid_reb$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
```



***
<!-- **Does your institution currently require suspending enrolment in ICU studies?** (n = `r sum(!is.na(dat_redcap$policy))`) (Question added after start of the study) -->

```{r fig.height=2, fig.width=6, results = "hold", warning=FALSE}

# #require suspending enrolment in icu studies
# dat_redcap %>% 
#   filter(redcap_event_name %in% c("202003_arm_1", "202004_arm_1", "202005_arm_1", "202006_arm_1")) %>%
#   mutate(Month = recode(redcap_event_name, 
#                         "202003_arm_1" = "March 2020", 
#                         "202004_arm_1" = "April 2020", 
#                         "202005_arm_1" = "May 2020",
#                         "202006_arm_1" = "June 2020"),
#          Month = fct_inorder(Month)) %>%
#   select(Month, "Yes - All studies" = policy___1, "Yes - All non-COVID-19 studies" = policy___2 , "Yes - Some studies" = policy___3, "No" = policy___4, "Other" = policy___5) %>%
#   mutate_at(c("Yes - All studies", "Yes - All non-COVID-19 studies", "Yes - Some studies", "Other"), 
#             as.numeric) %>%
#   group_by(Month) %>%
#   summarise_at(c("Yes - All studies", "Yes - All non-COVID-19 studies", "Yes - Some studies", "Other"),sum, na.rm= TRUE) %>%
#   kable(align = "c")

#TABLE FOR THIS QUESTION

#Types of Studies that were affected?
#dat_redcap %>% 
  #select(Comments = policy_some_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

#Please explain the other requirements
#dat_redcap %>% 
  #select(Comments = policy_other) %>% 
  #drop_na(Comments) %>% 
  #kable()

```

***     
<!--tab 4------------------------------------------------------->  
## Impact on research  
***

**Because of COVID-19 or preparation for it, has your ICU:**  

**Suspended recruitment for any studies?** (n = `r sum(!is.na(dat_redcap$effect_suspend))` surveys)
```{r fig.height=6, fig.width=6, results = "hold"}
ggplot(monthly_effect_suspend) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_suspend), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_suspend$xcent, labels = monthly_effect_suspend$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#dat_redcap %>% 
  #select(Comments = effect_suspend_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

```
***
**Modified recruitment for current studies?** (n = `r sum(!is.na(dat_redcap$effect_modify))` surveys)

```{r fig.height=6, fig.width=6, results = "hold"}
ggplot(monthly_effect_modify) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_modify), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_modify$xcent, labels = monthly_effect_modify$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic


#Comments
#dat_redcap %>% 
  #select(Comments = effect_modify_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

```
***
**Delayed the initiation of new (non-COVID-19) studies?** (n = `r sum(!is.na(dat_redcap$effect_delay))` surveys)

```{r fig.height=6, fig.width=6, results = "hold", warning=FALSE}
ggplot(monthly_effect_delay) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_delay), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_delay$xcent, labels = monthly_effect_delay$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments
#dat_redcap %>% 
  #select(Comments = effect_delay_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

```

***
**Enrolled MORE patients in studies because of increased patient volume?** (n = `r sum(!is.na(dat_redcap$effect_more))` surveys)

```{r fig.height=6, fig.width=6, results = "hold", warning=FALSE}
ggplot(monthly_effect_more) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_more), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_more$xcent, labels = monthly_effect_more$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments ADD THIS BACK IN IF THERE ARE COMMENTS
#dat_redcap %>%
  #select(Comments = effect_more_explain) %>%
  #drop_na(Comments) %>%
  #kable()

```

***
**Enrolled FEWER patients in studies because of increased patient volume?** (n = `r sum(!is.na(dat_redcap$effect_less))` surveys)

```{r fig.height=6, fig.width=6, results = "hold"}
ggplot(monthly_effect_less) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_less), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_less$xcent, labels = monthly_effect_less$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments
#dat_redcap %>% 
  #select(Comments = effect_less_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

```

***
**Changed the approach to co-enrollment in studies?** (n = `r sum(!is.na(dat_redcap$effect_co))` surveys)	

```{r fig.height=6, fig.width=6, results = "hold", warning=FALSE}
ggplot(monthly_effect_co) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_co), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_co$xcent, labels = monthly_effect_co$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments
#dat_redcap %>% 
  #select(Comments = effect_co_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

```

***
**Changed or stopped collection of biologic samples?** (n = `r sum(!is.na(dat_redcap$effect_bio))` surveys)

```{r fig.height=6, fig.width=6, results = "hold"}
ggplot(monthly_effect_bio) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_bio), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_bio$xcent, labels = monthly_effect_bio$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#Comments
#dat_redcap %>% 
  #select(Comments = effect_bio_explain) %>% 
  #drop_na(Comments) %>% 
  #kable()

```

***
**Other effects on studies in your ICU?** (n = `r sum(!is.na(dat_redcap$effect_other_yn))` surveys)

```{r fig.height=6, fig.width=6, results = "hold", warning=FALSE}
ggplot(monthly_effect_other_yn) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = effect_other_yn), 
            colour = "white", size = 1) +
  scale_fill_manual(name = "", values = c("#82CA9D", "#FFF79A", "#F7977A"), guide = guide_legend(reverse = FALSE))+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_effect_other_yn$xcent, labels = monthly_effect_other_yn$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
#Comments
#dat_redcap %>% 
  #select(Comments = effect_other) %>% 
  #drop_na(Comments) %>% 
  #kable()

```
  
 
<!--tab 5------------------------------------------------------->  
***  
## Reasons for impact    

***
**Because of COVID-19 or preparation for it, how much of an effect have the following had on research in your ICU?**

**Research staff WITH a clinical background are needed to work clinically** (n = `r sum(!is.na(dat_redcap$reason_clinwork))` surveys)

```{r fig.height=6, fig.width=6.5, results = "hold", warning=FALSE}

ggplot(monthly_reason_clinwork) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_clinwork), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_clinwork$xcent, labels = monthly_reason_clinwork$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
```

***
**Research staff WITHOUT a clinical background are needed to help with hospital activities** (n = `r sum(!is.na(dat_redcap$reason_work))` surveys)  
```{r fig.height=6, fig.width=6.5, results = "hold", warning=FALSE}

ggplot(monthly_reason_work) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_work), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_work$xcent, labels = monthly_reason_work$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

```
***
**Investigators are needed to work clinically** (n = `r sum(!is.na(dat_redcap$reason_clinwork_invest))` surveys) (Question added after start of the study)

```{r fig.height=6, fig.width=6.5, results = "hold", warning=FALSE}

ggplot(monthly_reason_clinwork_invest) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_clinwork_invest), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_clinwork_invest$xcent, labels = monthly_reason_clinwork_invest$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

```

***
**Research staff are concerned about their safety working during outbreak** (n = `r sum(!is.na(dat_redcap$reason_safety))` surveys)

```{r fig.height=6, fig.width=6.5, results = "hold"}
ggplot(monthly_reason_safety) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_safety), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_safety$xcent, labels = monthly_reason_safety$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

```
***
**Your pediatric ICU is admitting (or planning to admit) adults** (n = `r sum(!is.na(dat_redcap$reason_adults))` surveys) (Question added after start of the study)

```{r fig.height=6, fig.width=6.5, results = "hold"}

ggplot(monthly_reason_adults) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_adults), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_adults$xcent, labels = monthly_reason_adults$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

```

***
**Not enough research staff for increased number of COVID-19 studies** (n = `r sum(!is.na(dat_redcap$reason_numstudies))` surveys)

```{r fig.height=6, fig.width=6.5, results = "hold", warning=FALSE}
ggplot(monthly_reason_numstudies) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_numstudies), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_numstudies$xcent, labels = monthly_reason_numstudies$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
```

***
**Not enough research staff for increased number of eligible patients** (n = `r sum(!is.na(dat_redcap$reason_numpts))` surveys)

```{r fig.height=6, fig.width=6.5, results = "hold", warning=FALSE}
ggplot(monthly_reason_numpts) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_numpts), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_numpts$xcent, labels = monthly_reason_numpts$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
```

***
**Infection control policies limiting research staff access to the ICU** (n = `r sum(!is.na(dat_redcap$reason_accessicu))` surveys)

```{r fig.height=6, fig.width=6.5, results = "hold"}
ggplot(monthly_reason_accessicu) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_accessicu), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_accessicu$xcent, labels = monthly_reason_accessicu$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
```

***
**Infection control policies limiting research staff access to patients with confirmed or suspected COVID-19** (n = `r sum(!is.na(dat_redcap$reason_accesspt))` surveys)

```{r fig.height=6, fig.width=6.5, results = "hold"}
ggplot(monthly_reason_accesspt) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_accesspt), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_accesspt$xcent, labels = monthly_reason_accesspt$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
```

***
**Clinical staff are too busy to complete research-related tasks** (n = `r sum(!is.na(dat_redcap$reason_clinworkload))` surveys)

```{r fig.height=6, fig.width=6.5, results = "hold"}
ggplot(monthly_reason_clinworkload) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_clinworkload), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_clinworkload$xcent, labels = monthly_reason_clinworkload$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic
```

***
**Research facilities for processing or storage of biological samples are closed or have reduced capacity** (n = `r sum(!is.na(dat_redcap$reason_lab))` surveys) (Question added after start of the study)

```{r fig.height=6, fig.width=6.5, results = "hold"}

ggplot(monthly_reason_lab) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_lab), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_lab$xcent, labels = monthly_reason_lab$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

```

***
**COVID-19 specific research is prioritized over other research** (n = `r sum(!is.na(dat_redcap$reason_priorities))` surveys)

```{r fig.height=6, fig.width=6.5, results = "hold", warning=FALSE}
ggplot(monthly_reason_priorities) +
  geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = reason_priorities), 
            colour = "white", size = 1) +
  scale_fill_brewer(name = "", palette = "Blues", guide = guide_legend(reverse = TRUE), 
                    direction = -1)+
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     expand = c(0, 0)) +
  scale_x_continuous(breaks = monthly_reason_priorities$xcent, labels = monthly_reason_priorities$month,
                     expand = c(0, 0)) +
  coord_fixed() +
  theme_bw() + 
  theme_mosaic

#dat_redcap %>% 
  #select(Comments = reason_other) %>% 
  #drop_na(Comments) %>% 
  #kable()

```



<!--tab 7------------------------------------------------------->  
## To join this study 
***  
On behalf of the Canadian Critical Care Trials Group and Canadian Critical Care Research Coordinators group, we invite your site to participate in a short longitudinal survey of the effects of COVID-19 on critical care research. 


Use this link to send us the name and email of the person who will complete the survey on behalf of your centre:  http://bit.ly/3aNqo8Z  
They’ll receive a separate email with the survey within 24 hours and will get:  
1) A 3-question survey about your ICU  
2) A short (<10 min) monthly survey about the impact of COVID-19 on research in your ICU  

***  
## About this study

**Background:** As we prepare for and manage COVID-19 patients in our ICUs, we realize both the importance of studying this disease and our role as global leaders in critical care research.  From our experiences with SARS and H1N1, we also know that COVID-19 may both enhance and constrain current critical care research projects.  
  
**Objectives:** The aims of this study are to:  
1. Characterize current research activities in ICUs  
2. Describe the effects of COVID-19 (and preparations) on research in ICUs, specifically to: identify new research started due to COVID-19; describe any impact on existing research activities; and identify COVID-19 hospital or ICU policies affecting research. 
  
**Methods:** If you agree for your site to participate, you or your delegate will receive:  
•	A link to a single, brief survey (3 questions) about your ICU  
•	A link to a short (<10 minutes) survey about the impact of COVID-19 on research in your ICU. It will be sent on the first of the month for the duration of the COVID-19 outbreak.  
•	A report summarizing the results after each monthly survey  

**Ethics and privacy:** This study has been reviewed by the Hamilton Integrated Research Ethics Board. Participation is of course voluntary and submitting data implies your consent to participate . You can stop participating at any time and prior to analysis you can withdraw any data from your centre. We will not publish any site or personal identifying information without your express consent.  
  
Thank you, and we welcome any suggestions for adapting and updating this survey as events in this pandemic unfold.  
 
**Mark Duffett**, RPh PhD  
Departments of Pediatrics and Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada. duffetmc@mcmaster.ca, @[M_Duffett](http://twitter.com/M_Duffett)  
 
**Michelle Kho**, PT PhD  
School of Rehabilitation Science, McMaster University, Hamilton, Canada. khome@mcmaster.ca, @[khome](http://twitter.com/khome)  

 

